Intel Nervana has built a competitive deep learning platform to make it easy for data scientists to start from the iterative, investigatory phase and take models all the way to deployment. Nervana’s platform is designed for speed and scale, and serves as a catalyst for all types of organizations to benefit from the full potential of deep learning. Example of supported applications include but not limited to automotive speech interfaces, image search, language translation, agricultural robotics and genomics, financial document summarization, and finding anomalies in IoT data.
Andres Rodriguez at AI Frontiers: Catalyzing Deep Learning's Impact in the Enterprise
1. Catalyzing Deep Learning's
Impact in the Enterprise
Andres Rodriguez, PhD
January 11, 2017
AIFrontiers
[adapted from a talk by Arjun Bansal, Intel Nervana]
MAKING MACHINES
SMARTER.™
2. AI can transform the world for the better
2
SAFER HEALTHIER HAPPIER
3. But how does your enterprise win in this space?
3
4. 1. Use an existing model
4
SegNet
AIICNN
bAbI
Q&A
GoogLeNet
Alexnet
Deep
Speech 2
VGG
Sentiment Analysis
5. 2. Train with your data
5
http://vision.stanford.edu/Datasets/collage_s.png
https://www.kaggle.com/c/dogs-vs-cats
6. 2. Train with your data
6
http://vision.stanford.edu/Datasets/collage_s.png
http://adas.cvc.uab.es/task-cv2016/papers/0026.pdf
11. 6. If your org requires it - have an on premise plan
11
Buys and
provisions
enterprise brands
piecemeal
Managed with
VMware
Organized and
managed with
vblocks
Commodity
hardware +
OpenStack
Uses Public
Cloud
12. 6. …or go straight to a cloud service
12
Buys and
provisions
enterprise brands
piecemeal
Managed with
VMware
Organized and
managed with
vblocks
Commodity
hardware +
OpenStack
Uses Public
Cloud
SKIP UNNECESSARY SPENDING